Deep Learning | Machine Learning | Neural networks | CNN | Data Cleaning & Analysis
Service Description
- Create a Deep Learning model of Regression, Binary Classification, Single label multiclass classification, multilabel multiclass classification, Probability predictions model, Image Classification, and other DL/ML algorithms according to the problem of the client.
- Load and gather data from the web, and different file formats into python DataFrame. Then do preprocess, data cleansing, sorting, tackling NaN, applying the statistical approach, extracting useful features, do analysis on data and make it ready to be fed into the Deep Learning/ML model.
- Visualization of the result of the model would be complementary :)
Technology Used
I will use the following Tools and Software:
- Python
- TensorFlow & Keras
- Scikit-learn
- Numpy & Pandas
- Weka (data mining)
- Matplotlib & Seaborn
- Anaconda | Jupyter notebook | VS Code
- Git & GitHub
and other tools/software.
Frequently Asked Questions
Which DL/ML projects have I worked on in past?
Regression: Car & House price prediction and Cement strength prediction
Binary classification: Classifying movie reviews into positive or negative | Credit card fraud detection
Multiclass classification / Probability prediction: classify newsletters into 46 different classes AND classify product reviews into 10 categories.
Image Classification: Classifying 4 different flowers using CNN
What type of data Analysis will I do?
I will concatenate all data into DataFrame. Search for empty cells/NaN values, sort data, Normalize if in numeric form, One-Hot encoding if in string/char for different features/categories. Find correlation of features/attributes and prioritizes according to DL/ML problem. Convert to NumPy arrays in order to feed to DL/ML model.
If you have any other questions feel free to ask me :)
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